Evidence map›Paper›PMID 34685301›Full record

ArticlePolymers2021

Process Optimization for Manufacturing PAN-Based Conductive Yarn with Carbon Nanomaterials through Wet Spinning.

Hyelim Kim, Hyeongmin Moon, Daeyoung Lim, Wonyoung Jeong

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Hyelim KimMaterial and Component Convergence R&D Department, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Gyeonggi-do, Korea.ORCID 0000-0003-4880-7420
Hyeongmin MoonMaterial and Component Convergence R&D Department, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Gyeonggi-do, Korea.
Daeyoung LimMaterial and Component Convergence R&D Department, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Gyeonggi-do, Korea.
Wonyoung JeongMaterial and Component Convergence R&D Department, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Gyeonggi-do, Korea.ORCID 0000-0001-5643-1035
Korea Institute of Industrial Technology · KR

Funding

Gyeonggi-Do Technology Development Program kitech IZ-21-0001Korea Institute of Industrial Technology kitech JA-21-0001
6 · The paper itself

Abstract

This study aimed to manufacture PAN-based conductive yarn using a wet-spinning process. Two types of carbon nanomaterials, multiwall carbon nanotubes (MWCNT) and carbon nanofiber (CNF), were used alone or in a mixture. First, to derive the optimal composite solution condition for the wet spinning process, a composite solution was prepared with carbon nanomaterials of the same total mass weight (%) and three types of mechanical stirring were performed: mechanical stirring, ultra-sonication, and ball milling. A ball milling process was finally selected by analyzing the viscosity. Based on the above results, 8, 16, 24, and 32 wt% carbon nanomaterial/PAN composite solutions were prepared to produce wet spinning-based composite films before preparing a conductive yarn, and their physical and electrical properties were examined. By measuring the viscosity of the composite solution and the surface resistance of the composite film according to the type and content of carbon nanomaterials, a suitable range of viscosity was found from 10

Indexed as

conductive yarnelectrical propertyhybrid carbon nanofillermulti-wall carbon nanotubepoly(acrylonitrile)vapor grown carbon nanofiberwet spinning

Identifiers

PMID34685301
PMCPMC8537922
OpenAlexW3207211609

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.